15 citations · 17 across the 5 of their papers we have counts for
5 papers
Analytically-Driven Resource Management for Cloud-Native Microservices
Yanqi Zhang, Zhuangzhuang Zhou, Sameh Elnikety +1
Resource management for cloud-native microservices has attracted a lot of recent attention. Previous work has shown that machine learning (ML)-driven approaches outperform traditio…
Towards Fast, Adaptive, and Hardware-Assisted User-Space Scheduling
Lisa, Li, Nikita Lazarev +7
Modern datacenter applications are prone to high tail latencies since their requests typically follow highly-dispersive distributions. Delivering fast interrupts is essential to re…
A Hardware-Software Stack for Serverless Edge Swarms
Liam Patterson, David Pigorovsky, Brian Dempsey +6
Swarms of autonomous devices are increasing in ubiquity and size, making the need for rethinking their hardware-software system stack critical. We present HiveMind, the first swarm…
Sage: Leveraging ML to Diagnose Unpredictable Performance in Cloud Microservices
Yu Gan, Mingyu Liang, Sundar Dev +2
Cloud applications are increasingly shifting from large monolithic services, to complex graphs of loosely-coupled microservices. Despite their advantages, microservices also introd…
Sinan: Data Driven Resource Management for Cloud Microservices
Yanqi Zhang, Weizhe Hua, Zhuangzhuang Zhou +2
Cloud applications are increasingly shifting to interactive and loosely-coupled microservices. Despite their advantages, microservices complicate resource management, due to inter-…